Methods and apparatus for predictive failure analysis of a cooling device

ABSTRACT

The present disclosure relates to the monitoring of a cooling device. More specifically, the methods and apparatus for measuring efficiency of a cooling unit. Monitoring may be done through measurement of the electrical use of the cooling unit and additional environmental variables. This measurement may create a profile for the cooling unit that may be compared to historical performance of the unit itself, the expected performance of the same model or similar model, as well as a combination of both. These measurements may be used to create predictive analysis for expected future performance. These measurements may be used for comparison to the performance of a malfunctioning unit. These measurements may be used to determine when the unit is performing outside the expected range and therefore malfunctioning.

RELATED APPLICATIONS

This Patent Application claims the benefit of, and incorporates by reference as if set forth in full herein, U.S. Provisional Patent Application No. 62/110,854, filed on 2 Feb. 2015, titled METHODS AND APPARATUS FOR PREDICTIVE FAILURE ANALYSIS OF A COOLING DEVICE.

FIELD OF THE DISCLOSURE

The present disclosure relates to methods and apparatus for the measurement and collection of variable data. More specifically, the present disclosure presents a method of measuring changes in the efficiency of an electric motor and cooling device that may be integral to the operation of a refrigerator or freezer unit.

BACKGROUND OF THE DISCLOSURE

Traditionally, the method for diagnosing a malfunctioning cooling device is to follow a series of steps in diagnosis. Failures would be categorized, then organized into a list where the end user would find the specific symptom that the unit exhibits. Then the user would reference the symptom to the corresponding list of checks and possible problems. For example, if the freezer is not operating at an optimal temperature, the user may be instructed to check the condenser coils, the door seals, test the temperature control, and check for a refrigerant leak, etc.

The problem with this method is twofold. First, the user is limited to diagnosing failures that have already occurred rather than proactively addressing mechanical issues before they manifest symptoms. This diagnosis is generally limited to determining a mechanical issue by a change in cooling temperature. Second, diagnosis is dependent on the user having broad knowledge of the unit's operating components. While diagnosis may be a time consuming effort if the user has broad knowledge, it will particularly difficult for a user who is uninformed

As the end user has additional cooling needs the addition of new units becomes necessary. This increases the likelihood that additional model types or brands may be used. This multiplies the amount of necessary information the user must know to successfully diagnose and repair issues and substantially increases the difficulty of diagnosis.

SUMMARY OF THE DISCLOSURE

What is needed is a device that can intelligently record the performance characteristics of a cooling device and allow for the diagnosis of performance degradation or failure based on this data. Proactively addressing these issues is likely to save repair costs, prevent loss of service to the customer thereby allowing the user uninterrupted business, and finally to prevent spoilage.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, that are incorporated in and constitute a part of this specification, illustrate several embodiments of the disclosure and, together with the description, serve to explain the principles of the disclosure:

FIG. 1 illustrates an exemplary cooling unit with a predictive failure device, wherein the predictive failure device may be attached to the motor unit.

FIG. 2 illustrates an exemplary cooling unit with a predictive failure device, wherein the predictive failure device may be separate from the cooling unit and connected to the power source.

FIG. 3 illustrates exemplary method steps for collection and analysis of performance data.

FIG. 4 illustrates exemplary method steps for collecting and transmitting collected performance data to an external device for analysis, wherein the external device may return analyzed data to the predictive failure device for local display.

FIG. 5 illustrates an exemplary processing and interface system.

DETAILED DESCRIPTION

The present disclosure provides generally for a device to monitor the electrical efficiency of a cooling unit. This device may be used in conjunction with a display device or a communications network.

In the following sections, detailed descriptions of examples and methods of the disclosure will be given. The description of both preferred and alternative examples though thorough are exemplary only, and it is understood that to those skilled in the art that variations, modifications, and alterations may be apparent. It is therefore to be understood that the examples do not limit the broadness of the aspects of the underlying disclosure as defined by the claims.

GLOSSARY

-   -   Predictive Failure Device: as used herein refers to a device         that may actively predict failure of a cooling device, such as a         refrigerator or freezer. In some embodiments, the predictive         failure device may comprise one or more a monitoring mechanism,         analyzing mechanism, and measuring mechanism, wherein the         mechanisms may manage data acquired from the cooling device. In         some embodiments, the management of the data may allow the         predictive failure device to actively track the efficiency         and/or operational quality of the cooling device and/or its         components. In some embodiments, the data may comprise the         electrical usage of a cooling unit.     -   Performance Information: as used herein refers to accumulated         data that may be processed to assess the performance of a         cooling unit.     -   Performance Profile: as used herein refers to performance         information and other data used to create an expected range of         performance under set circumstances for a cooling unit.

Referring now to FIG. 1, an exemplary embodiment of a predictive failure device 100 affixed to a cooling unit 110, wherein the predictive failure device 100 may be integrated to measure the efficiency of cooling unit 125, is illustrated. In some aspects, the predictive failure device 100 may be fully or partially integrated into the interior of the cooling unit 110. The predictive failure device 100 may measure the current flowing from the power source 105. In some embodiments, the predictive failure device 100 may measure the current flowing to the device and the current returned to the power source 105. In some other aspects, the predictive failure device 100 may measure the current flowing from the power source 105, the current returned to the power source 105, or any combination thereof.

The collection of data in FIG. 1 may include, in any combination, data input from a sensor cluster 115 measuring the interior temperature of the cooling unit 125 and the exterior temperature of the cooling unit 125, as well as the interior humidity level of the cooling unit 125 and the exterior humidity level of the cooling unit 125. Furthermore, door open/close sensor 120 may provide data about the instances and duration of door 130 openings. This additional sensor information may be gathered by the monitoring unit either through wired or wireless communication.

In some embodiments, the predictive failure device may comprise a monitoring mechanism, which may be programmed to monitor a predefined quality set. The predefined quality set may comprise characteristics of one or more the cooling device or a component within the cooling device, wherein the characteristics may be indicative of the effectiveness and/or efficiency of one or more the cooling device or a component within the cooling device. In some aspects, the predefined quality set may comprise one or more of current, temperature within the cooling device, temperature of one or more electrical components, electricity usage.

In some implementations, the monitoring mechanism may receive data regarding the predefined quality and may detect fluctuations that may indicate a decrease in effectiveness and/or efficiency, which may lead to a failure of the cooling device and/or a component of the cooling device. In some embodiments, the predictive failure device may further comprise an analyzing mechanism, which may analyze the monitored data, wherein the analysis may assess and/or quantify the effectiveness and/or efficiency. The analysis may further predict when the cooling device or the component may fail if no adjustments or repairs are made. In some aspects, the monitored data may be transmitted to an external device, which may execute the analysis.

Referring now to FIG. 2, an exemplary embodiment of a predictive failure device 200 independently located from the cooling unit 225, wherein the predictive failure device 200 may measure the efficiency of the cooling unit 225, is illustrated. The predictive failure device 200 may measure the current flowing from the power source 205 to the cooling apparatus 210. In some other examples, the predictive failure device 200 may measure the current flowing to the device and the current returned to power source 205, or any combination thereof.

The collection of data in FIG. 2 may also include in any combination data input from a sensor cluster 215 measuring the interior temperature of the cooling unit 225 and the exterior temperature of the cooling unit 225 as well as the interior humidity level of the cooling unit 225 and the exterior humidity level of the cooling unit 225. Furthermore door open/close sensor 220 may provide data about the instances and duration of door 230 openings. This additional sensor information may be gathered by the monitoring unit either through wired or wireless communication.

Referring now to FIG. 3, exemplary method steps for the collection, analysis, and display of data are illustrated. In some embodiments at 305, performance data may be received for example from a sensor. The source of the Sensor output data may comprise but is not limited to sensors detecting electrical use, temperature, humidity, and door openings.

In some embodiments at 310, performance data may optionally be received from a user, wherein a user may comprise a manager, technician or owner. Optional performance data may comprise any data that the user may input through the display device or directly into the data collection center, for example.

In some embodiments at 310, performance data may comprise data inputted into the system about a malfunctioning status of a door, which may allow the door to only partially close. In some embodiments, the predictive failure device may analyze the system as malfunctioning and therefore emit an alarm. The user may prefer to change the measured parameters to adjust for the malfunctioning door, wherein the adjustment may allow the user to continue to use the predictive failure device without receiving alarms.

In some embodiments at 315, data may be stored, wherein the data may be accessible for future use.

In some embodiments at 320, the performance data may be stored for long term storage. In some implementations, this data may be used to create a profile of the cooling unit's performance over the lifetime of the unit. In some embodiments, the performance data may be used to create a performance profile of the cooling unit.

In some embodiments at 325, the performance profile of the cooling unit may be accessed. In some implementations, the performance profile may comprise the expected performance characteristics of the unit during various malfunctions.

In some embodiments at 330, performance data may be analyzed using various methods to determine the current performance of the cooling unit. In some embodiments, analysis may comprise an assessment of an expected range of power consumption for a performance level of the cooling unit, wherein the assessment may determine when the performance may be outside the expected range, and the unit may be malfunctioning or in need of a service. In some implementations, analysis may compute from the historic performance of the cooling unit for the historic performance of the cooling unit during a time of day, a calendar day, or a combination of both. In some embodiments, analysis may be based on an efficiency rating that may compute the expected peak efficiency performance of the unit and the cooling unit's actual performance in comparison to the efficiency rating. In some embodiments, analysis may also involve an aggregation of occurrences of the door opening categorized by a twenty four hour clock or by calendar day. In some embodiments, analysis may utilize predictive modeling to estimate future performance.

In some embodiments at 335, analyzed performance data may be displayed to the user in a manner that may provide useful, accurate, and understandable information. Examples of data display devices may comprise electronic display devices, IPAD, tablet device, analog display, and lights. Some embodiments of displaying results may require user authentication to access the information. Some embodiments of displaying results may also require additional hardware interface to display results.

Referring now to FIG. 4, exemplary method steps for transmission of data to an external device, wherein analysis of the performance data may be performed by the external device, are illustrated. In some embodiments at 405, performance data may be received for example from a sensor. In some embodiments at 410, performance data may optionally be received from a user, wherein a user may comprise a manager, technician or owner. In some embodiments at 415, data may be stored, wherein the data may be accessible for future use. In some embodiments at 420, the performance data may be stored for long term storage.

In some embodiments at 430, data may be transmitted to an external device. In some implementations, data may be transmitted through internet protocol (IP), through cellular communication, or through both. In some implementations, there may be a battery back up to allow the transmission of data to an external device during a power outage. In some embodiments at 435, data may be received from an external device.

Referring now to FIG. 5, an exemplary processing and interface system 500 is illustrated. In some aspects, access devices 515, 510, 505, such as a predictive failure device 505, a mobile device 515 or laptop computer 510 may be able to communicate with an external server 525 though a communications network 520. The external server 525 may be in logical communication with a database 526, which may comprise data related to identification information and associated profile information. In some examples, the server 525 may be in logical communication with an additional server 530, which may comprise supplemental processing capabilities.

In some aspects, the server 525 and access devices 505, 510, 515 may be able to communicate with a cohost server 540 through a communications network 520. The cohost server 540 may be in logical communication with an internal network 545 comprising network access devices 541, 542, 543 and a local area network 544. For example, the cohost server 540 may comprise a payment service, such as PayPal or a social network, such as Facebook or a dating website.

CONCLUSION

A number of embodiments of the present disclosure have been described. While this specification contains many specific implementation details, there should not be construed as limitations on the scope of any disclosures or of what may be claimed, but rather as descriptions of features specific to particular embodiments of the present disclosure.

Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in combination in multiple embodiments separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous.

Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

Thus, particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order show, or sequential order, to achieve desirable results. In certain implementations, multitasking and parallel processing may be advantageous. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the claimed disclosure. 

What is claimed is:
 1. A predictive failure device for a cooling apparatus comprising: a monitoring mechanism configured to monitor a predefined quality set of the cooling apparatus, wherein the predefined quality set comprises characteristics indicative of an effectiveness of at least one component of the cooling apparatus; a communications network access device configured to access a server in logical communication with a digital communications network; and executable software stored on the communications network access device and executable on demand, the software operative with the communications network access device to cause the network access device to: receive data for the predefined quality set; and transmit the data to an external server.
 2. The predictive failure device of claim 1, wherein the network access device is further caused to analyze the received data for the predefined quality set.
 3. The predictive failure device of claim 2, wherein the network access device is further caused to analyze the received data for the predefined quality set.
 4. The predictive failure device of claim 1 further comprising an analyzing mechanism configured to analyze the data for the predefined quality set, wherein the analysis determines the effectiveness of the at least one component of the cooling apparatus. 